Ink model generation mechanism

ABSTRACT

A printing system is disclosed. The printing system includes at least one physical memory device to store drop size logic and one or more processors coupled with the at least one physical memory device to execute the drop size logic to generate drop size data associated with a printing system based on ink deposition data for a print medium and ink drop count data.

FIELD OF THE INVENTION

The invention relates to the field of printing systems, and inparticular, to performing ink usage estimation for a printing system.

BACKGROUND

Some print systems estimate ink usage assuming a constant volume for inkdrops ejected from the printhead. However, ink volumes ejected by theprinthead tend to vary over time and during printing due to changes inthe print environment or conditions of the ink or printhead.Accordingly, ink estimates that assume constant ejection amounts areinaccurate. Determining accurate ink model parameter estimates andcomputing actual ink drop sizes for a printer are complicated processesthat may take large amounts of time to perform.

Performing those determinations typically requires printing a range ofprint jobs while measuring ink volumes and ink drop counts for eachprint job. Further, these determinations apply only to the specificprint mediums, print settings and printers that are to be evaluated.Because these processes are arduous, efficient mechanisms to determineaccurate ink model parameter estimates and computing ink drop sizes aredesired.

SUMMARY

In one embodiment, a printing system is disclosed. The printing systemincludes at least one physical memory device to store drop size logicand one or more processors coupled with at least one physical memorydevice to execute the drop size logic to generate drop size dataassociated with a printing system based on ink deposition data for aprint medium and ink drop count data.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the present invention can be obtained from thefollowing detailed description in conjunction with the followingdrawings, in which:

FIG. 1 is a block diagram of one embodiment of a printing system;

FIGS. 2A&2B illustrate block diagrams of embodiments of a printcontroller;

FIG. 2C illustrates another embodiment of an ink model logic and dropsize logic implemented in a network;

FIG. 3 illustrates one embodiment of ink model logic;

FIG. 4 is a flow diagram illustrating one embodiment of an ink modelcomputation process;

FIG. 5 illustrates one embodiment of drop size logic;

FIG. 6 illustrates one embodiment of a graph of uncalibrated dropfractions as a function of gray level;

FIG. 7 is a flow diagram illustrating one embodiment of a drop sizecomputation process; and

FIG. 8 illustrates one embodiment of a computer system.

DETAILED DESCRIPTION

A mechanism for determining ink model parameter estimates and using theestimates to compute drop sizes is described. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth to provide a thorough understanding of the presentinvention. It will be apparent, however, to one skilled in the art thatthe present invention may be practiced without some of these specificdetails. In other instances, well-known structures and devices are shownin block diagram form to avoid obscuring the underlying principles ofthe present invention.

Reference in the specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the invention. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment.

FIG. 1 is a block diagram illustrating one embodiment of a printingsystem 130. A host system 110 is in communication with the printingsystem 130 to print a sheet image 120 onto a print medium 180 via aprinter 160 (e.g., print engine). Print medium 180 may include paper,card stock, paper board, corrugated fiberboard, film, plastic,synthetic, textile, glass, composite or any other tangible mediumsuitable for printing. The format of print medium 180 may be continuousform or cut sheet or any other format suitable for printing. Printer 160may be an ink jet, electrophotographic or another suitable printer typehaving a well-defined association with the amount of marking materialdeposited in each individual printer picture element (pel).

In one embodiment, printer 160 comprises one or more print heads 162,each including one or more pel forming elements 165 that directly orindirectly (e.g., by transfer of marking material through anintermediary) forms the representation of picture elements (pels) on theprint medium 180 with marking material (e.g., ink, paint, toner,polymers and other materials suitable for printing) applied (e.g.,deposited) to the print medium. In an ink jet printer, the pel formingelement 165 is a tangible device (e.g., an ink jet nozzle) that ejectsthe ink drop 170 (e.g., marking material elements) onto the print medium180 and, in an electro-photographic (EP) printer the pel forming elementmay be a tangible device that determines the location of toner particlesprinted on the print medium (e.g., an EP exposure LED or an EP exposurelaser).

The pel forming elements may be grouped onto one or more printheads. Thepel forming elements 165 may be stationary (e.g., as part of astationary printhead) or moving (e.g., as part of a printhead that movesacross the print medium 180) as a matter of design choice. The pelforming elements 165 may be assigned to one of one or more color planesthat correspond to types of marking materials (e.g., Cyan, Magenta,Yellow, and blacK (CMYK)).

In a further embodiment, printer 160 is a multi-pass printer (e.g., dualpass, 3 pass, 4 pass, etc.) wherein multiple sets of pel formingelements 165 print the same region of the print image on the printmedium 180. The set of pel forming elements 165 may be located on thesame physical structure (e.g., an array of nozzles on an ink jet printhead) or separate physical structures. The resulting print medium 180may be printed in color and/or in any of a number of gray shades,including black and white (e.g., Cyan, Magenta, Yellow, and blacK,(CMYK)). The host system 110 may include any computing device, such as apersonal computer, a server, or even a digital imaging device, such as adigital camera or a scanner.

The sheet image 120 may be any file or data that describes how an imageon a sheet of print medium 180 should be printed. For example, the sheetimage 120 may include PostScript data, Printer Command Language (PCL)data, and/or any other printer language data. The print controller 140processes the sheet image to generate a bitmap 150 for transmission.Bitmap 150 may be a halftoned bitmap (e.g., a calibrated halftone bitmap generated from calibrated halftones, or uncalibrated halftone bitmap generated from uncalibrated halftones) for printing to the printmedium 180. The printing system 130 may be a high-speed printer operableto print relatively high volumes (e.g., greater than 100 pages perminute).

The print medium 180 may be continuous form paper, cut sheet paper,and/or any other tangible medium suitable for printing. The printingsystem 130, in one generalized form, includes the printer 160 thatpresents the bitmap 150 onto the print medium 180 (e.g., via toner, ink,etc.) based on the sheet image 120. Although shown as a component ofprinting system 130, other embodiments may feature printer 160 as anindependent device communicably coupled to print controller 140.

The print controller 140 may be any system, device, software, circuitryand/or other suitable component operable to transform the sheet image120 for generating the bitmap 150 in accordance with printing onto theprint medium 180. In this regard, the print controller 140 may includeprocessing and data storage capabilities. In one embodiment, measurementmodule 190 is implemented as part of ink model and ink drop size systemsto obtain measurements of the printed medium 180. The measured resultsare communicated to print controller 140 to be used to generate inkmodel parameter data, as well as generate drop size data. Themeasurement module 190 may be a stand-alone process communicably coupledto printing system 130 or be integrated into the printing system 130.

According to one embodiment, measurement module 190 may be a sensor totake measurements of printed images on print medium 180. Measurementmodule 190 may generate and transmit print image measurement data. Printimage measurement data may be color response (e.g., RGB, opticaldensity, etc.) data corresponding to a printed image that is either rawor processed. In one embodiment, measurement module 190 may comprise oneor more sensors that each or in total take measurements for printedmarkings produced for some or all pel forming elements 165. In-line inkvolume sensing devices to monitor the amount (e.g., volume or mass) ofink used for printing is another type of device which may be included inmeasurement module 190.

In another embodiment, measurement module 190 may be a camera system,in-line scanner, densitometer or spectrophotometer. In a furtherembodiment, print image measurement data may include map information tocorrelate portions (e.g., a pel or plurality of pels) of the print imagedata to the corresponding pel forming elements 165 that produced theportions of the printed images.

FIGS. 2A&2B illustrate embodiments implementing print controller 140.FIG. 2A illustrates a print controller 140 (e.g., DFE or digital frontend), in its generalized form, including ink model logic 220, drop sizelogic 230, and ink estimation logic 240. FIG. 2B illustrates anembodiment in which print controller 140 includes drop size logic 230and ink estimation logic 240, while ink model logic 220 are coupledexternally. In either embodiment, the separate components may representhardware used to implement the print controller 140. Alternatively, oradditionally, the separate components may represent logical blocksimplemented by executing software instructions in a processor of theprinter controller 140.

Although shown as a component within of print controller 140, otherembodiments may feature ink model logic 220 and drop size logic 230included within independent devices, or combination of devices,communicably coupled to print controller 140. For instance, FIG. 2Cillustrates one embodiment of ink model logic 220 and drop size logic230 implemented in a network 280. As shown in FIG. 2C, ink model logic220 and drop size logic 230 are included within a computing systems 260and 270, respectively, and transmit data to printing system 130 via acloud network 290.

According to one embodiment, ink model logic 220 generates ink modelparameter data for an unknown print medium based on uncalibrated inkdeposition data for a reference print medium and uncalibrated opticaldensity (OD) measurement data for the unknown print medium printed on aprint system (e.g., printing system 130). In such an embodiment, theuncalibrated ink deposition data associated with the reference printmedium is generated from reference ink model parameter data for thereference print medium and uncalibrated optical density measurement datafor the reference print medium.

FIG. 3 illustrates one embodiment of ink model logic 220. As shown inFIG. 3 , ink model logic 220 includes ink deposition generation logic310 and ink model generation logic 320. According to one embodiment, inkdeposition generation logic 310 generates the uncalibrated inkdeposition data associated with the reference print medium based onreceived reference ink model parameter data. In such an embodiment, thereference ink model parameter data comprises a one-time generation ofink model parameter data for the reference print medium.

In one embodiment, ink model parameter data (e.g., reference or unknown)comprises parameter estimates that are generated by applying an inkmodel, such as a Weibull ink model regression, to describe a functionalrelationship between OD and ink deposition data. Weibull cumulativedistribution function (CDF) describes the probability that a real-valuedrandom variable X with a given probability will be found at a value lessthan or equal to x (where x is a one possible value of the randomvariable X). Intuitively, it is the “area under the curve” function ofthe probability density function (PDF). Cumulative distributionfunctions are also used to specify the distribution of multivariaterandom variables. The Weibull CDF model that is employed uses twoparameters.

In one embodiment, the Weibull CDF is modified to incorporate paperwhite and the solid area maximum optical density. This modified WeibullCDF will be described as simply “Weibull CDF”. The forward Weibull CDFrelates ink deposition to OD, while the inverse Weibull CDF relates ODto ink deposition. In one embodiment, ink deposition is represented by:

${{{Ink}{Deposition}} = \frac{{Total}{Ink}{Mass}}{Area}},{{{Total}{Ink}{Mass}} = {\sum\limits_{Area}{{Drop}{sizes}}}}$

In one embodiment, a four parameter Weibull ink model is implementedusing OD=(p(3)*(1−exp^(((−(x/p(1)){circumflex over ( )}p(2)))))+p(4). Insuch an embodiment, the two-parameter classical Weibull CDF function hasbeen extended to four parameters to create an ink model. The twoadditional parameters allow the model to account for paper white andabsolute paper referenced OD, where x=ink deposition mass per area,p(1)=ink mass per area scale factor, which is similar to the classicalWeibull scale factor , and p(2)=slope factor.

This factor influences the shape of the function similarly to theclassical Weibull slope factor, p(3)=maximum paper referenced OD andp(4)=paper white OD. Factors p(1) and p(2) are the parameters used inthe classical two parameter Weibull CDF function. The p(1) scale factoradjusts the shape of the curve to modify how much ink deposition isrequired to achieve various ODs. Larger values for p(1) require more inkdeposition to achieve the same OD.

In addition, since p(1) is similar to two-parameter classical Weibullslope, it indicates the point of the curve where the ink depositioncorresponds to the OD level approximately 63% between the range definedby the paper referenced OD, parameter p(3) and the OD defined by p(4).The model provides a value for the maximum absolute OD for theink/paper. This maximum OD will be given by the sum of the p(3) and p(4)parameters. This maximum OD would occur at infinite ink deposition.

Based on the Weibull CDF parameters, OD ink response data may begenerated using uncalibrated ink deposition data. In other embodiments,the response data may be represented using CIE L*a*b* rather than OD. Insuch an embodiment, CIE L*a*b* is implemented to provide Delta Ecalculations, Alternate ink models, like the Weibull model describedpreviously, can be used to describe the relationship between CIE L*a*b*and ink deposition. For example L* versus ink deposition can use thesame equation, by modifying the definitions for p(3) and p(4) to use L*values instead of OD. The alternate model predicts decreased L* valueswith increased ink deposition x. A polynomial function, alone orcombined with a Weibull like equation, can be used to describe a* and b*vs ink deposition.

Uncalibrated OD measurement data comprises OD response data measuredfrom a print medium. In one embodiment, the OD response data comprisesan OD versus digital count, where digital count is the gray levelrepresenting the pels in the bitmap 150. Uncalibrated ink deposition (orink deposition) is defined as an average amount of ink deposited perprinted device pel, where a pel is a picture element of the printer 160(e.g., the printing device).

In a further embodiment, the amount of ink deposition changes as afunction of digital count. In such an embodiment, the pels in bitmap 150range from 0-255 for a typical 8-bit system. Additionally, the digitalcount is a control parameter of an output pel. In yet a furtherembodiment, an ink deposition curve is the ink deposition (e.g., amountof ink per area) defined over the range of all possible gray levels(e.g., 0-255). In such an embodiment, ink deposition is computed on anaverage basis to eliminate local variations due to halftoning using aset of discrete drop sizes. An area equal to the printed size of thehalftone threshold array is a good region to use for the areacalculation, since it defines the size of the fundamental halftonepatterns. Ink drop sizes may be determined by analyzing the amount ofink used and counts of ink drops of each size, as will be discussed inmore detail below.

According to one embodiment, the reference ink model parameter data maybe generated from an uncalibrated OD measurement data for the referencemedium and an uncalibrated ink deposition may be generated from measureddrop sizes and halftone drop fractions generated for test print jobs(e.g., printed and measured at printing system 130, or another printingsystem)

Once the reference ink model parameter data has been received at inkmodel logic 220, the reference print medium is installed, and one ormore test print jobs may be printed, at printing system 130. As aresult, measurement module 190 measures uncalibrated OD measurement dataof test data printed to the reference print medium. The uncalibrated ODmeasurement data for the reference print medium may then be received atink model logic 220.

Uncalibrated ink deposition data for the reference print medium isgenerated based on the reference ink model parameter data and theuncalibrated OD measurement data for the reference print medium (seedetails further below). Subsequently, the process may be repeated withan unknown print medium being installed at printing system 130, and oneor more test print jobs being printed to the unknown print medium.

Again, measurement module 190 measures uncalibrated OD measurement datafor printed test data, this time for the unknown print medium. Theuncalibrated OD measurement data for the unknown print medium may thenbe received at ink model logic 220. In one embodiment, ink modelgeneration logic 320 generates the ink model parameter data (e.g., viathe Weibull ink model regression) for the unknown print medium based onuncalibrated ink deposition data for the reference print medium usinginverse Weibull ink model and the uncalibrated optical density (OD)measurement data for the unknown print medium.

FIG. 4 is a flow diagram illustrating one embodiment of a process 400for performing an ink model computation. Process 400 may be performed byprocessing logic that may include hardware (e.g., circuitry, dedicatedlogic, programmable logic, microcode, etc.), software such asinstructions run on a processing device, or a combination thereof. Inone embodiment, process 400 is performed by ink model logic 220.

According to one embodiment, process 400 begins at processing block 410,where ink model parameter data is received for the reference printmedium. At processing block 420, the reference print medium is installedat printing system 130, where one or more test print jobs are printed onthe reference print medium. At processing block 430, uncalibrated ODmeasurement data is received for the test print jobs printed on thereference medium (e.g., form measurement module 190).

At processing block 440, uncalibrated ink deposition data is generatedfor the reference print medium, based on the OD measurement data for thereference print medium and inverse ink model for the reference printmedium. At processing block 450, an unknown print medium is installed atprinting system 130, where one or more test print jobs are printed onthe unknown print medium.

At processing block 460, uncalibrated OD measurement data is receivedfor the test print jobs printed on the unknown medium. At processingblock 470, ink model parameter data for the unknown print medium isgenerated based on the OD measurement data for the unknown medium andthe ink deposition data for the reference print medium by using theinverse ink model for the reference print medium. At processing block480, the ink model parameter data for the unknown print medium istransmitted. It should be understood that measurements and inkdepositions for like digital count values are used to obtain matchingsets of data to generate the ink model parameters for the unknownmedium. By performing this, ink model parameter data for the unknownprint medium has been determined efficiently and with minimal systemresources. Ink model parameter data may be used to determine ink dropsizes and/or ink usage estimation in a print system 130.

Referring back to FIGS. 2A-2C, drop size logic 230 is implemented togenerate ink drop sizes for printing system 130. In one embodiment, dropsize logic 230 uses the ink model parameter data received from ink modellogic 220 to generate the drop size data. FIG. 5 illustrates oneembodiment of drop size logic 230, including ink deposition generationlogic 510 and drop size generation logic 520.

Ink deposition generation logic 510 generates uncalibrated inkdeposition data using (or based on) ink model parameter data anduncalibrated OD measurement data. In one embodiment, the uncalibrated ODmeasurement data is associated with OD measurements generated tocalibrate print heads 162 of printer 160 (FIG. 1 ). In a furtherembodiment, the uncalibrated ink deposition data is generated using aninverse of the Weibull ink model (or inverse ink model).

As discussed above, the Weibull ink model refers to OD and inkdepositions using measured drop sizes e.g., OD=W(i)=M(ID⁻¹(i)), where Wis the Ink Model W(i) as a function of ink deposition i, M(g) is theMeasured OD as a function of gray level g and ID is the uncalibrated inkdeposition as a function of gray level. Thus, the inverse Weibull may beused to determine the uncalibrated ink deposition from the uncalibratedOD vs gray level g (e.g., W⁻¹(OD)=ID(M⁻¹(OD)). This defines both the ODand Ink deposition ID relationships versus gray level, whereas the inkmodel does not include this relationship.

It should be clear that while the ink model is referred to as a Weibullink model, the ink model can be any functional relationship whichrelates OD to ink deposition for a printer. The inverse ink model beingan inverse relationship requires a single value to provide a one to onerelationship between ink deposition and OD. This one to one relationshipfor inverse functions is commonly described by the horizontal line test.

In our application to derive the ink model for an unknown paper, we haveW₁ ⁻¹(OD)=ID₁(g). This employs the inverse of the ink model W₁ for thereference paper to generate a function vs gray level g to describe theink deposition ID₁ for the reference paper. Measuring OD as a functionof gray level g using the unknown paper to establish M₂, we then canderive an ink model W₂ for the unknown paper using the relationshipW₂(i)=M₂(ID₁ ⁻¹(i)). This produces a function W₂, which describes theink model for the unknown paper. Again, since we have inverse functions,we must require them to pass the horizontal line test to ensure that aone to one relationship exists. In the case of the Ink depositionfunction ID this is generally guaranteed by the halftone design whichrequires the stacking condition that always has a larger drop size forevery pel as the gray level is increased. This produces a monotonicallyincreasing level of ink deposition for increasing gray level which isknown to meet the horizontal line test.

Drop size generation logic 520 generates drop size data based on theuncalibrated ink deposition data at ink deposition generation logic 510.According to one embodiment, drop size generation logic 520 uses theuncalibrated ink deposition (or UID) data and ink drop count data (e.g.,uncalibrated drop fractions) to generate the drop size data. Ink dropcount data comprises a number of drops that occur at each of theplurality of gray levels. Uncalibrated drop fractions may be received bydrop size logic 230. Drop fractions represent the ratio of number ofdrops for a given drop size, relative to the total number of possibledrops of all sizes. Drop fractions are expressed as a function vs graylevel.

FIG. 6 illustrates one embodiment of a graph of uncalibrated dropfractions as a function of gray level for a four-drop size halftone,where the drop fraction range is between zero and one. The dropfractions for each individual drop size, including none, must always sumto a value of one since drops must be one of four different drop sizes.

In one embodiment, the uncalibrated drop fraction data is generatedbased on analysis of an uncalibrated halftone. A calibrated halftone isa halftone that has been adjusted to achieve a target response and so anuncalibrated halftone has not been adjusted to achieve a targetresponse. Uncalibrated drop fractions represent percentages of ahalftone threshold array for a specific drop size at each digital count(DC) level, where digital count is the gray level representing the pelsin the bitmap 150, which ranges from 0-255 for a typical 8 bit system.DC is a print system input control and print system input control may berepresented as DC, percent dot, or gray level.

To determine the uncalibrated drop fractions, an uncalibrated multibitthreshold array may be analyzed to determine a number of drops (e.g.,drop count) that occur at each DC or gray level. Thus, uncalibrated dropfractions are the number of drops in the threshold array for one dropsize (e.g., small, medium, large and none) divided by the total numberof drops for the one drop size in the threshold array, which isdetermined for each different drop size at each DC level.

The total number of drops for a single drop size is defined by the sizeof the threshold array. The total number of drops for a single drop sizeis the product of the number of rows and the number of columns in thethreshold array. For example, at DC level 100, if we have 10000 smalldrops and the array is 256×256, the uncalibrated small drop fraction is10000/(256*256) or 0.153. The uncalibrated drop fraction for the nonedrop size is not necessary to compute. It can be used for verificationsince the sum of all uncalibrated drop fractions including none must beequal to one (100%). Uncalibrated drop fraction may be determined foreach color plane based on the uncalibrated multibit thresholdcorresponding to each color plane.

In one embodiment, UID=W⁻¹(OD_measured), provided inverse Weibullfunction=W⁻¹; measured OD=OD_measured; unknown drop sizes=DS_small,DS_medium and DS_large; Gray level=g; and uncalibrated drop fractionsfor small, medium and large drops: UDF_small(g), UDF_medium(g), andUDF_large(g). In a further embodiment, the ink model and the ODmeasurement data are for matching conditions. In other words, the inkmodel used must be for the same paper, halftone and ink set that wasused to measure the OD. Ink models described previously for a referenceprint medium or unknown print medium may be used. Thus, assuming afour-drop size system (e.g., none, small, medium and large):Ink deposition perpel=(UDF_small(g)*DS_small)+(UDF_medium(g)*DS_medium)+(UDF_large(g)*DS_large);andInk deposition per area=Ink deposition per pel/Area of pel

Based on the above, drop size generation logic 520 determines best fitdrop sizes to obtain an ink deposition per area that equals theuncalibrated ink deposition. In one embodiment, generation logic 520determines the best fit drop sizes by performing a drop size regression.In such an embodiment, a least squares regression process is performedto solve the set of linear equations and obtain the unknown drop sizes.

Using the regression process, ink depositions are determined for eachgray level. Based on a set of 256 (e.g., 0-255) simultaneous linearequations of uncalibrated ink deposition values, three equations areimplemented to define three unknown drop sizes. Thus, approximatelyeighty-five (e.g., (256/3) sets of three different drop sizes may bedetermined, enabling an understanding of how drop sizes change acrossthe tonal range (e.g., assuming an 8-bit halftone). Employing higher bitdepth halftones permits obtaining a larger set of drop size estimates byemploying the regression process for each pattern of the halftone. Forexample, a 14 bit halftone enables deriving drop sizes at each graylevel for an 8 bit imaging path.

In yet a further embodiment, drop size generation logic 520 is alsoimplemented to determine drop sizes for printer characteristics otherthan gray levels since drop sizes may vary depending on such conditions.In such an embodiment, drop size generation logic 520 may determine dropsizes for printer characteristics of print system 130, such as patchsizes, printhead voltages (PHV), printhead temperatures, jettingfrequencies, number of jetting nozzles, other system temperatures,and/or etc.

FIG. 7 is a flow diagram illustrating one embodiment of a process 700for performing a drop size computation. Process 700 may be performed byprocessing logic that may include hardware (e.g., circuitry, dedicatedlogic, programmable logic, microcode, etc.), software such asinstructions run on a processing device, or a combination thereof. Inone embodiment, process 700 is performed by drop size logic 230.

According to one embodiment, process 700 begins at processing block 710,where ink model parameter data is received. As discussed above, the inkmodel parameter data may be received from ink model logic 220. Atprocessing block 720, the uncalibrated OD measurement data is received.In one embodiment, the uncalibrated OD measurement data is generated byprint engine calibration.

At processing block 730, uncalibrated ink deposition data is generatedusing the uncalibrated OD measurement data and ink model parameter data(e.g., via inverse Weibull). At processing block 740, the drop size datais generated based on the uncalibrated ink deposition data (e.g., via aregression using drop fractions). At processing block 750, the drop sizedata is transmitted. In one embodiment, the transmitted drop size datamay be displayed at a graphical user interface (GUI) 250 at printcontroller 140.

At decision block 760, a determination is made as to whether one or morechanges to characteristics of print system 130 has been detected. If so,control is returned to processing block 720 where the process isrepeated for updated uncalibrated OD measurement data generated inresponse to the change in the print system 130 characteristics.Otherwise, control remains at decision block 760 until a change tocharacteristics of print system 130 has been detected.

Referring to FIGS. 2A-2C, ink estimation logic 240 is implemented toprovide an estimation of ink that is to be used to produce a print job.In such an embodiment, ink estimation logic 220 generates estimated inkusage data by computing a sum of ink usage data for each of a pluralityof drop sizes generated by each pel forming element 165. In a furtherembodiment, ink estimation logic 220 uses histograms generated for eachcolor plane (e.g., CMYK), as well as the drop size data and dropfractions, to estimate the print job ink usage. By performing this, inkdrop size and/or ink estimation is determined accurately, efficientlyand with minimal system resources. Ink drop size data may be used toevaluate and determine ink usage estimation in a print system 130.

FIG. 8 illustrates a computer system 1000 on which printing system 130,print controller 140, ink model logic 220, drop size logic 230 and/orink estimation logic 240 may be implemented. Computer system 1000includes a system bus 1020 for communicating information, and aprocessor 1010 coupled to bus 1020 for processing information.

Computer system 1000 further comprises a random access memory (RAM) orother dynamic storage device 1025 (referred to herein as main memory),coupled to bus 1020 for storing information and instructions to beexecuted by processor 1010. Main memory 1025 also may be used forstoring temporary variables or other intermediate information duringexecution of instructions by processor 1010. Computer system 1000 alsomay include a read only memory (ROM) and or other static storage device1026 coupled to bus 1020 for storing static information and instructionsused by processor 1010.

A data storage device 1027 such as a magnetic disk or optical disc andits corresponding drive may also be coupled to computer system 1000 forstoring information and instructions. Computer system 1000 can also becoupled to a second I/O bus 1050 via an I/O interface 1030. A pluralityof I/O devices may be coupled to I/O bus 1050, including a displaydevice 1024, an input device (e.g., an alphanumeric input device 1023and or a cursor control device 1022). The communication device 1021 isfor accessing other computers (servers or clients). The communicationdevice 1021 may comprise a modem, a network interface card, or otherwell-known interface device, such as those used for coupling toEthernet, token ring, or other types of networks.

Embodiments of the invention may include various steps as set forthabove. The steps may be embodied in machine-executable instructions. Theinstructions can be used to cause a general-purpose or special-purposeprocessor to perform certain steps. Alternatively, these steps may beperformed by specific hardware components that contain hardwired logicfor performing the steps, or by any combination of programmed computercomponents and custom hardware components.

Elements of the present invention may also be provided as amachine-readable medium for storing the machine-executable instructions.The machine-readable medium may include, but is not limited to, floppydiskettes, optical disks, CD-ROMs, and magneto-optical disks, ROMs,RAMs, EPROMs, EEPROMs, magnetic or optical cards, propagation media orother type of media/machine-readable medium suitable for storingelectronic instructions. For example, the present invention may bedownloaded as a computer program which may be transferred from a remotecomputer (e.g., a server) to a requesting computer (e.g., a client) byway of data signals embodied in a carrier wave or other propagationmedium via a communication link (e.g., a modem or network connection).

The following clauses and/or examples pertain to further embodiments orexamples. Specifics in the examples may be used anywhere in one or moreembodiments. The various features of the different embodiments orexamples may be variously combined with some features included andothers excluded to suit a variety of different applications. Examplesmay include subject matter such as a method, means for performing actsof the method, at least one machine-readable medium includinginstructions that, when performed by a machine cause the machine toperform acts of the method, or of an apparatus or system according toembodiments and examples described herein.

Some embodiments pertain to Example 1 that includes a system comprisingat least one physical memory device to store drop size logic and one ormore processors coupled with the at least one physical memory device toexecute the drop size logic to generate drop size data associated with aprinting system based on ink deposition data for a print medium and inkdrop count data.

Example 2 includes the subject matter of Example 1, wherein the dropsize data is generated by performing a drop size regression.

Example 3 includes the subject matter of Examples 1 and 2, wherein thedrop size regression determines a best fit of drop sizes for a pluralityof gray levels to determine an ink deposition per area equal to the inkdeposition data.

Example 4 includes the subject matter of Examples 1-3, wherein the inkdrop count data comprises a number of drops that occur at each of theplurality of gray levels.

Example 5 includes the subject matter of Examples 1-4, whereingenerating the ink deposition data comprises applying an inverse of inkmodel parameter data to an optical density data.

Example 6 includes the subject matter of Examples 1-5, wherein the dropsize data is generated based on a plurality of print systemcharacteristics.

Example 7 includes the subject matter of Examples 1-6, wherein the printsystem characteristics comprise at least one of gray levels, patchsizes, printhead voltage and printhead temperature.

Example 8 includes the subject matter of Examples 1-7, wherein the inkestimation logic further transmits the drop size data.

Example 9 includes the subject matter of Examples 1-8, furthercomprising a graphical user interface to display the drop size data.

Some embodiments pertain to Example 10 that includes a method comprisinggenerating drop size data associated with a printing system based on inkdeposition data for a print medium and ink drop count data.

Example 11 includes the subject matter of Example 10, wherein the dropsize regression determines a best fit of drop sizes for a plurality ofgray levels to determine an ink deposition per area equal to the inkdeposition data.

Example 12 includes the subject matter of Examples 10 and 11, whereinthe ink drop count data comprises a number of drops that occur at eachof the plurality of gray levels.

Example 13 includes the subject matter of Examples 10-12, whereingenerating the ink deposition data comprises applying an inverse of inkmodel parameter data to an optical density data.

Example 14 includes the subject matter of Examples 10-13, wherein thedrop size data is generated based on a plurality of print systemcharacteristics.

Example 15 includes the subject matter of Examples 10-14, wherein theprint system characteristics comprise at least one of gray levels, patchsizes, printhead voltage and printhead temperature.

Some embodiments pertain to Example 16 that includes at least onecomputer readable medium having instructions stored thereon, which whenexecuted by one or more processors, cause the processors to generatedrop size data associated with a printing system based on ink depositiondata for a print medium and ink drop count data.

Example 17 includes the subject matter of Example 16, wherein the dropsize data is generated by performing a drop size regression.

Example 18 includes the subject matter of Examples 16 and 17, whereinthe drop size regression determines a best fit of drop sizes for aplurality of gray levels to determine an ink deposition per area equalto the ink deposition data.

Example 19 includes the subject matter of Examples 16-18, wherein theink drop count data comprises a number of drops that occur at each ofthe plurality of gray levels.

Example 20 includes the subject matter of Examples 16-19, whereingenerating the ink deposition data comprises applying an inverse of inkmodel parameter data to an optical density data.

Whereas many alterations and modifications of the present invention willno doubt become apparent to a person of ordinary skill in the art afterhaving read the foregoing description, it is to be understood that anyparticular embodiment shown and described by way of illustration is inno way intended to be considered limiting. Therefore, references todetails of various embodiments are not intended to limit the scope ofthe claims, which in themselves recite only those features regarded asessential to the invention.

What is claimed is:
 1. A system comprising: at least one physical memorydevice to store drop size logic; and one or more processors coupled withthe at least one physical memory device to execute the drop size logicto generate drop size data associated with a printing system based onink deposition data for a print medium and ink drop count data, whereinthe drop size data comprises ink drop sizes ejected by the printingsystem onto the print medium for each of a plurality of gray levels andis generated by performing a drop size regression that determines a bestfit of drop sizes for the plurality of gray levels to determine an inkdeposition per area equal to the ink deposition data.
 2. The system ofclaim 1, wherein the ink drop count data comprises a number of dropsthat occur at each of the plurality of gray levels.
 3. The system ofclaim 1, wherein generating the ink deposition data comprises applyingan inverse of ink model parameter data to an optical density data. 4.The system of claim 1, wherein the drop size data is generated based ona plurality of print system characteristics.
 5. The system of claim 4,wherein the print system characteristics comprise at least one of graylevels, patch sizes, printhead voltage and printhead temperature.
 6. Thesystem of claim 1, wherein the drop size logic further transmits thedrop size data.
 7. A method comprising: generating drop size dataassociated with a printing system based on ink deposition data for aprint medium and ink drop count data, wherein the drop size datacomprises ink drop sizes ejected by the printing system onto the printmedium for each of a plurality of gray levels and is generated byperforming a drop size regression that determines a best fit of dropsizes for the plurality of gray levels to determine an ink depositionper area equal to the ink deposition data.
 8. The method of claim 7,further comprising transmitting the drop size data.
 9. The method ofclaim 7, wherein the ink drop count data comprises a number of dropsthat occur at each of the plurality of gray levels.
 10. The method ofclaim 7, wherein generating the ink deposition data comprises applyingan inverse of ink model parameter data to an optical density data. 11.The method of claim 7, wherein the drop size data is generated based ona plurality of print system characteristics.
 12. The method of claim 11,wherein the print system characteristics comprise at least one of graylevels, patch sizes, printhead voltage and printhead temperature.
 13. Atleast one non-transitory computer readable medium having instructionsstored thereon, which when executed by one or more processors, cause theprocessors to: generate drop size data associated with a printing systembased on ink deposition data for a print medium and ink drop count data,wherein the drop size data comprises ink drop sizes ejected by theprinting system onto the print medium for each of a plurality of graylevels and is generated by performing a drop size regression thatdetermines a best fit of drop sizes for the plurality of gray levels todetermine an ink deposition per area equal to the ink deposition data.14. The computer readable medium of claim 13, having instructions storedthereon, which when executed by one or more processors, further causethe processors to transmit the drop size data.
 15. The computer readablemedium of claim 13, wherein the ink drop count data comprises a numberof drops that occur at each of the plurality of gray levels.
 16. Thecomputer readable medium of claim 15, wherein generating the inkdeposition data comprises applying an inverse of ink model parameterdata to an optical density data.